Dimension Reduction of Virtual Coordinate Systems in Wireless Sensor Networks

Abstract

Virtual Coordinate System (VCS) based routing schemes for sensor networks characterize each node by a coordinate vector of size M, consisting of distances to each of a set of M anchors. Higher the number of anchors, the higher the coordinate generation cost as well as the communication cost. Identifying an effective set of anchors and encapsulating original VCS's information in a lower dimensional VCS will enhance the energy efficiency. Two main contributions toward this goal are presented. First is a method for evaluating the amount of novel information contained in an ordinate, i.e., in an anchor, on the coordinate space created by the rest of the anchors. This method can be used to identify unnecessary or inefficient anchors as well as good anchor locations, and thus help lower overhead and power consumption in routing. Second, a method for reducing the VCS dimensionality is presented. This Singular Value Decomposition (SVD) based method preserves the routability achieved in original coordinate space but with lower dimensions. Centralized and online realizations of the proposed algorithm are explained. Examples of different topologies with 40 anchors used in performance analysis show that coordinate length can be reduced on average by a factor of 8 without degrading the routability. Use of novelty filtering to select effective anchors prior to SVD based compression results in further improvement in routability.